Standardized symptom screening: Cancer Care Ontario's expanded prostate cancer index composite for clinical practice (EPIC-CP) provincial implementation approach.
Bibliographic record
Abstract
100 Background: Cancer Care Ontario endorses patient reported outcome measures to improve outcomes and experience for nearly 14 million Ontarians. The EPIC-CP tool, validated to screen/monitor symptoms and side-effects in men with localized prostate cancer, was selected to improve patient and provider experience, and facilitate symptom management. Two pilots tested EPIC-CPs feasibility and acceptability. Subsequent recommendations include: province-wide implementation, improving technological privacy, patient and provider education and communication processes. This abstract will describe the provincial strategy for implementation of EPIC-CP. Methods: The implementation approach involved stakeholder-driven practices based on Kotter’s organizational process framework. Clinical, technical, administrative and patient stakeholder representatives from 14 cancer centres formed working groups to create a climate for change, to engage centres to strategize locally, to implement and sustain change and to address the challenges identified by the EPIC-CP pilot. Results: The final pilot ended in June 2015, and executive endorsement for EPIC-CP provincial implementation in March 2016. A schedule for multi-site phased implementation was informed by stakeholder consultations and began in Oct 2016. Technological privacy improvements were informed by 95 representatives creating a multidisciplinary team tasked with provincial oversight, development of EMR guidelines and IT solutions. Five patient and five clinical educational guides were designed to assist in symptom management, each focusing on one domain of EPIC-CP. Creation of the guides drew on the clinical and scientific expertise among 12 clinicians of varying disciplines in collaboration with four patients. This team assisted in enhancing communication processes by designing 21 training materials, including FAQs and narrated guides, accessible on a central communications hub. Conclusions: Results indicate that this framework-based, stakeholder-driven approach was successful and could be applied to other wide-scale implementations of symptom management tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".